Cyberhaven Labs released its 2026 AI Adoption & Risk Report, drawing from billions of real-world data movements across Generative AI SaaS applications, endpoint AI tools, and AI agents. The findings highlight rapid but fragmented enterprise AI adoption, exposing new data risks that legacy security technologies struggle to detect or govern.
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"What this research makes clear is that enterprise AI adoption isn't just accelerating, it's fragmenting," said Nishant Doshi, CEO of Cyberhaven. "A small set of teams is moving fast and embedding AI deeply into daily work, while security and governance are often playing catch-up. As organizations plan for 2026 and beyond, the risk isn't AI itself; it's not understanding how AI is actually being used. Without visibility into which tools are in play, what data is flowing through them, and where controls need to adapt, enterprises risk widening the gap between innovation and trust."
Coding Assistants and AI Agents Form the Second Wave AI coding assistants such as Cursor, GitHub Copilot, and Claude Code continued steady growth through 2025. In frontier companies, nearly 90% of developers rely on these tools, making them 11.5 times more likely to adopt than developers in lagging organizations. By late 2025, 30% of users reported employing at least two such assistants, signaling deepening integration into development workflows.
Most GenAI SaaS Tools Carry Elevated Risk Despite widespread use, the majority of popular GenAI SaaS applications fail to meet traditional enterprise risk benchmarks. High rates of sensitive data entry—through prompts or copy-paste actions—combined with personal account usage create blind spots for security teams. This behavior underscores the need for contextual visibility beyond conventional DLP approaches.
"AI is no longer a side experiment for most enterprises; it's becoming a core part of the infrastructure," added Doshi. "Organizations that succeed will be those that move beyond one-size-fits-all policies and invest in security approaches that reflect real usage patterns. By bringing visibility, context, and control together, enterprises can enable teams to innovate with AI while maintaining trust, compliance, and resilience as adoption continues to evolve."
The report highlights the growing divide between innovation speed and governance maturity, particularly in development, operations, and knowledge work. Addressing these gaps requires security solutions that align with actual AI behaviors rather than outdated assumptions.
Cyberhaven recently announced the general availability of its Data Security Posture Management solution, designed to protect sensitive data across endpoints, SaaS, cloud, on-premises environments, and AI workflows as part of its unified platform.
About Cyberhaven
Cyberhaven protects sensitive data wherever it lives and goes. Built for the AI era, Cyberhaven's unified data security platform combines DSPM, data loss prevention, insider risk management, and AI security with deep data lineage and agentic AI. Cyberhaven helps organizations stop data loss, reduce insider risk, and enable AI adoption securely, without slowing their business.
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